Modelling carbonaceous aerosol from residential solid fuel burning with different assumptions for emissions
- 1School of Chemistry, University of Edinburgh, Edinburgh, UK
- 2Natural Environment Research Council, Centre for Ecology & Hydrology, Penicuik, UK
- 3School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Manchester, UK
- 4Aerodyne Research, Inc., Billerica, MA, USA
- 5National Centre for Atmospheric Science, University of Manchester, Manchester, UK
- 6School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- 7School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
- 8School of GeoSciences, University of Edinburgh, Edinburgh, UK
- 9MRC PHE Centre for Environment and Health, King's College London, London, UK
- 10TNO, Department of Climate, Air and Sustainability, Utrecht, the Netherlands
- 11University of Exeter Medical School, European Centre for Environment and Health, Knowledge Spa, Truro, UK
- anow at: Clinical Surgery, University of Edinburgh, Edinburgh, UK
- bnow at: Air Quality Research Center, University of California, Davis, CA, USA
- cnow at: Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
Abstract. Evidence is accumulating that emissions of primary particulate matter (PM) from residential wood and coal combustion in the UK may be underestimated and/or spatially misclassified. In this study, different assumptions for the spatial distribution and total emission of PM from solid fuel (wood and coal) burning in the UK were tested using an atmospheric chemical transport model. Modelled concentrations of the PM components were compared with measurements from aerosol mass spectrometers at four sites in central and Greater London (ClearfLo campaign, 2012), as well as with measurements from the UK black carbon network.
The two main alternative emission scenarios modelled were Base4x and combRedist. For Base4x, officially reported PM2.5 from the residential and other non-industrial combustion source sector were increased by a factor of four. For the combRedist experiment, half of the baseline emissions from this same source were redistributed by residential population density to simulate the effect of allocating some emissions to the smoke control areas (that are assumed in the national inventory to have no emissions from this source). The Base4x scenario yielded better daily and hourly correlations with measurements than the combRedist scenario for year-long comparisons of the solid fuel organic aerosol (SFOA) component at the two London sites. However, the latter scenario better captured mean measured concentrations across all four sites. A third experiment, Redist – all emissions redistributed linearly to population density, is also presented as an indicator of the maximum concentrations an assumption like this could yield.
The modelled elemental carbon (EC) concentrations derived from the combRedist experiments also compared well with seasonal average concentrations of black carbon observed across the network of UK sites. Together, the two model scenario simulations of SFOA and EC suggest both that residential solid fuel emissions may be higher than inventory estimates and that the spatial distribution of residential solid fuel burning emissions, particularly in smoke control areas, needs re-evaluation. The model results also suggest the assumed temporal profiles for residential emissions may require review to place greater emphasis on evening (including
discretionary) solid fuel burning.